ArticleJournal of digital imaging2021
Quantitative Three-Dimensional Assessment of the Pharmacokinetic Parameters of Intra- and Peri-tumoural Tissues on Breast Dynamic Contrast-Enhanced Magnetic Resonance Imaging.
Article in Journal of digital imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictive value of background parenchymal enhancement on breast magnetic resonance imaging for pathological tumor response to neoadjuvant chemotherapy in breast cancers: a systematic review.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Pooled it
- Hybrid [Bioengineering (Basel, Switzerland) · 2026Article
- Development of an Automated CAD System for Lesion Detection in DCE-MRI.Journal of imaging informatics in medicine · 2025Article
- Analysis of dynamic contrast-enhanced T1-weighted imaging parameters in type II TIC breast lesions.Frontiers in oncology · 2025Article
- Prediction of lymphovascular invasion in invasive breast cancer based on clinical-MRI radiomics features.BMC medical imaging · 2024Article
- Effect of Neoadjuvant Chemotherapy on Angiogenesis and Cell Proliferation of Breast Cancer Evaluated by Dynamic Enhanced Magnetic Resonance Imaging.BioMed research international · 2022Article
- Predictive Value of Preoperative Dynamic Contrast-Enhanced MRI Imaging Features in Breast Cancer Patients with Postoperative Recurrence Time.Emergency medicine international · 2022Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We aimed to assess the feasibility of three-dimensional (3D) segmentation and to investigate whether semi-quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters are associated with traditional prognostic factors for breast cancer. In addition, we evaluated whether both intra-tumoural and peri-tumoural DCE parameters can differentiate the breast cancers that are more aggressive from those that are less aggressive. Consecutive patients with newly diagnosed invasive breast cancer and structural breast MRI (3.0 T) were included after informed consent. Fifty-six patients (mean age, 57 years) with mass lesions of > 7 mm in diameter were included. A semi-automatic image post-processing algorithm was developed to measure 3D pharmacokinetic information from the DCE-MRI images. The kinetic parameters were extracted from time-signal curves, and the absolute tissue contrast agent concentrations were calculated with a reference tissue model. Markedly, higher intra-tumoural and peri-tumoural tissue concentrations of contrast agent were found in high-grade tumours (n = 44) compared to low-grade tumours (n = 12) at every time point (P = 0.006-0.040), providing positive predictive values of 90.6-92.6% in the classification of high-grade tumours. The intra-tumoural and peri-tumoural signal enhancement ratios correlated with tumour grade, size, and Ki67 activity. The intra-observer reproducibility was excellent. We developed a model to measure the 3D intensity data of breast cancers. Low- and high-grade tumours differed in their intra-tumoural and peri-tumoural enhancement characteristics. We anticipate that pharmacokinetic parameters will be increasingly used as imaging biomarkers to model and predict tumour behavior, prognoses, and responses to treatment.
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